Evidence map›Paper›PMID 38173196›Full record

ArticleCurrent medicinal chemistry2024

Integrating Single-cell and Bulk RNA-seq to Construct a Metastasis-related Model for Evaluating Immunotherapy and Chemotherapy in Uveal Melanoma.

Yue Du, Xue Jiang, Yanyan Zhang, Jianing Ying, Quanyong Yi

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Article in Current medicinal chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yue DuPharmacy Department of Ningbo Eye Hospital, Wenzhou Medical University, Ningbo, 315040, China.
Xue JiangOphthalmology Department of Ningbo Eye Hospital, Wenzhou Medical University, Ningbo, 315040, China.
Yanyan ZhangOphthalmology Department of Ningbo Eye Hospital, Wenzhou Medical University, Ningbo, 315040, China.
Jianing YingOphthalmology Department of Ningbo Eye Hospital, Wenzhou Medical University, Ningbo, 315040, China.
Quanyong YiOphthalmology Department of Ningbo Eye Hospital, Wenzhou Medical University, Ningbo, 315040, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetastasis is a major cause of death in UM, highlighting the need to use highly specific and sensitive prognostic markers to identify patients with a risk of developing metastasis.

aimsThe aim of this study was to improve the current precision treatment for patients with metastatic uveal melanoma (UM).

objectiveThe objective of this work was to investigate the heterogeneity between primary human UM and metastatic UM at the single-cell level and to discover potential molecules regulating UM metastasis.

methodsSeurat R toolkit was employed to analyze single-cell sequencing data of UM and to identify differentially expressed genes (DEGs) between primary and metastatic UM. Least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were performed on the DEGs from the bulk RNA-seq cohort to develop a prognostic model. Based on the model, patients were divided into high and low groups. The correlations among the risk score, immune indicators, immune checkpoint blockade (ICB) therapy, and anti-tumor drug therapy were analyzed.

resultsCell types in primary UM and metastatic UM tumors include B/plasma cells, endothelial cells, melanocytes, monocytes/macrophages, photoreceptor cells, and T cells. Among 157 DEGs between the two tumor types, S100A4, PDE4B, CHCHD10, NSG1, and C4orf48 were selected to construct a prognostic model. The model could accurately and independently predict response to ICB treatment and sensitivity to antineoplastic drugs for UM patients as well as their immune infiltration levels, risk of death, and metastasis possibility.

conclusionsThis study analyzed the tumor ecosystem of primary and metastatic UM, providing a metastasis-related model that could be used to evaluate the prognosis, risk of metastasis, immunotherapy, and efficacy of antineoplastic drug treatment of UM.

Indexed as

ImmunotherapyMelanomaRNA-SeqSingle-Cell AnalysisUveal NeoplasmsAntineoplastic AgentsHumansNeoplasm MetastasisPrognosisUveal MelanomaAntineoplastic Agentsantineoplastic drugsanti-tumor.immunotherapymetastasistumor microenvironmentUveal melanoma

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.